Copyright: © 2015 |Pages: 24
DOI: 10.4018/978-1-4666-8116-3.ch011


In this chapter, students are presented with two distinct methods of choosing which units of analysis that represent a broader population will be included in a study. Multiple probability and non-probability sampling techniques are discussed. Upon reading this chapter, students will understand how to draw a random sample and the inherent advantages of probability sampling methods compared to non-probability methods. Concepts such as sampling frame, generalizability, margin of error, and confidence level are discussed. Numerous examples are used throughout.
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What Is Sampling?

Sampling is a means of making a researcher’s workload manageable. It is the process by which you choose a predetermined number of units of analysis for inclusion in your study. Sampling is choosing. When sampling, you begin with a larger population of your unit of analysis, and from there you systematically carve out a sliver of that population. The sample is just that – a small representation of a larger population. In the context of research methods, the population will always be a “collection” of whatever your unit of analysis is. The sample is the systematic process by which you choose x number of units of analysis from that larger collection. Figures 1 and 2 illustrate what sampling entails.

Figure 1.

Sampling process I

Figure 2.

Sampling process II

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